Browsing by Subject "Nitrogen"

Now showing 1 - 4 of 4
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    Estimation of nitrogen content in cucumber plant (Cucumis sativus L.) leaves using hyperspectral imaging data with neural network and partial least squares regressions
    (Elsevier, 2021-10-15) Sabzi, Sajad; Pourdarbani, Razieh; Rohban, Mohammad H.; García Mateos, Ginés; Arribas, J. I.; Informática y Sistemas; Facultades de la UMU::Facultad de Informática
    In recent years, farmers have often mistakenly resorted to overuse of chemical fertilizers to increase crop yield. However, excessive consumption of fertilizers might lead to severe food poisoning. If nutritional deficiencies are detected early, it can help farmers to design better fertigation practices before the problem becomes unsolvable. The aim of this study is to predict the amount of nitrogen (N) content in cucumber (Cucumis sativus L., var. Super Arshiya-F1) plant leaves using hyperspectral imaging (HSI) techniques and three different regression methods: a hybrid artificial neural networks-particle swarm optimization (ANN-PSO); partial least squares regression (PLSR); and unidimensional deep learning convolutional neural networks (CNN). Cucumber plant seeds were planted in 20 different pots. After growing the plants, pots were categorized and three levels of nitrogen overdose were applied to each category: 30%, 60% and 90% excesses, called N30%, N60%, N90%, respectively. HSI images of plant leaves were captured before and after the application of nitrogen excess. A prediction regression model was developed for each individual category. Results showed that mean regression coefficients (R) for ANN-PSO were inside 0.937–0.965, PLSR 0.975–0.997, and CNN 0.965–0.985 ranges, test set. We conclude that regression models have a remarkable ability to accurately predict the amount of nitrogen content in cucumber plants from hyperspectral leaf images in a non-destructive way, being PLSR slightly ahead of CNN and ANN-PSO methods.
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    Influence of hydrological processes on spatial pattern of nitrogen in an arid stream of southeast Spain.
    (2010-07-30) García García, Victoria; Gómez, Rosa; Vidal-Abarca Gutiérrez, María Rosario; Suárez Alonso, María Luisa; Ecología e Hidrología
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    Modelling of photosynthesis, respiration and nutrients yield coefficients in Scenedemus almeriensis culture as a function of nitrogen and phosphorus.
    (2021-09-14) Gómez serrano, Cintia; Acién Fernández, Francisco Gabriel; Fernández Sevilla, José María; Molina Grima, Emilio; Sánchez Zurano, Ana; Ingeniería Química
    Se aplicaron técnicas foto-respirométricas para evaluar la actividad fotosintética en organismos fototróficos. Estos métodos permiten analizar la respuesta fotosintética bajo diferentes condiciones. En este trabajo, se estudió la influencia de la disponibilidad de nutrientes (nitrato, amonio y fosfato) en la fotosíntesis y la respiración de Scenedesmus almeriensis mediante mediciones foto-respirométricas cortas. Tanto la fotosíntesis como la respiración aumentaron hasta un valor de saturación y posteriormente disminuyeron, mostrando inhibición a concentraciones altas. En cuanto a la influencia de la concentración de fósforo en las células de microalgas, se observó una tendencia hiperbólica similar, aunque no se detectó inhibición a concentraciones elevadas. A partir de estos datos experimentales, las tasas de respiración y fotosíntesis de S. almeriensis se modelaron utilizando la ecuación de Haldane para los datos de nitrato y amonio, y la ecuación de Monod para los datos de fosfato. Además, se realizaron experimentos para determinar los coeficientes de rendimiento de nitrógeno y fósforo en los cultivos de S. almeriensis. Los resultados mostraron que estos coeficientes no son constantes y se modifican según la concentración de nutrientes, evidenciando el fenómeno de absorción de lujo. Finalmente, los modelos propuestos se incorporaron en una herramienta de simulación para evaluar la actividad fotosintética y los coeficientes de rendimiento de nutrientes de S. almeriensis cuando se utilizan diferentes medios de cultivo y aguas residuales como fuente de nitrógeno y fósforo para su crecimiento.
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    Optimizing Chlorella vulgaris production and exploring its impact on germination through microalga-N2-fixing bacteria consortia
    (Elsevier, 2025-10-01) Sánchez Zurano, Ana; Vilaró Cos, Silvia; Figueiredo, Daniel; Melkonyan, Lusine; Ferreira, Alice; Acién, Francisco Gabriel; Lafarga, Tomás; Gouveia, Luisa; Ingeniería Química; Facultades de la UMU::Facultad de Química
    Microalgal biomass is increasingly valued in industrial and agricultural sectors due to its bioactive compounds. However, large-scale production remains costly, mainly due to nitrogen fertilizer expenses. A promising sustainable alternative is co-cultivation with N2-fixing bacteria, capable of supplying biologically available nitrogen. In this study, Chlorella vulgaris was grown in synthetic medium with and without nitrogen, as well as in co-culture with three different N2-fixing bacteria in nitrogen-free medium. Microalgal growth was assessed by dry weight, Fv/Fm ratio, and flow cytometry, which also allowed evaluation of population dynamics and cell viability. Biomass composition (proteins, carbohydrates, lipids, chlorophyll, and carotenoids) was analyzed under all conditions. Co-cultures in nitrogen-free medium showed comparable biomass productivity to nitrogen-supplemented controls, although Fv/Fm values indicated physiological stress in some cases. Moreover, the agricultural potential of the resulting biomass and supernatants was evaluated through germination bioassays using lettuce seeds. All cultures tested at 0.2 g·L−1 significantly improved the germination index. Also, applying the culture supernatant (biomass removed) also yielded positive effects, with GI increases exceeding 40 %. These results suggest that co-cultivation with N2-fixing bacteria can support efficient microalgal production while generating biomass and supernatants with biostimulant potential, contributing to sustainable agriculture and circular bioeconomy strategies.